Data is the new petroleum; companies need better pipelines — and better oil-spill clean-up methods

Data powers the 21st-century economy in the same way that petroleum did last century — but there’s one key difference, today the producers and users of this vital resource are one and the same. These days, every organization is pumping out data by the barrel and investing mightily in ways to refine and use it to fuel business momentum.

But often, companies fail to fully protect data as the key resource it is, despite its critical role in day-to-day operations. Data disruptions, much like an oil spill, can halt business in its tracks. While enterprises are spending billions of dollars to try to keep bad actors from compromising their networks, what happens when the hackers inevitably infiltrate the IT environment?  

Without the right systems in place to back up and restore proprietary information, the big investments that companies are making in advanced analytics, automation, and artificial intelligence are at risk. If data is the 21st-century oil, businesses need better storage tanks and more secure, better-designed pipelines. It’s all part of a continuous-business mindset that recognizes the risks of any data outage.  

As these assets become more valuable, so does the incentive for hackers always looking for ways to exploit vulnerabilities and force companies to pay multi-million-dollar data ransoms. As AI technology stacks evolve, an approach centered on data resiliency ensures that a company’s most vital source of “energy” is adequately safeguarded and available to power the next decade of growth.   

From Big Data to Better Data  

In the past, “data” in an organization meant carefully organized tables of information. But today, the term encompasses everything from those highly curated assets to raw, unfiltered and unstructured information spanning documents, social media posts, video and audio files, and the like. And instead of using data to only answer questions like, “What were my sales last quarter?” companies now want to better predict what’s ahead, automate operations, and offer all employees new levels of business intelligence.  

To achieve those benefits, businesses are increasingly investing in efforts to unify data from many systems. By adding the necessary security and governance protocols, they can then begin to use the information to drive business value. But this is no longer about just dumping data into a single repository and hoping for the best. Most analytics platforms don’t have the capacity to sift through massive datasets and extract only the most relevant, actionable insights.  

AI, for example, needs real-time access to high-quality data tailored for specific use cases. If the data is incomplete or inaccurate, application performance could suffer, perhaps even churning out false or misleading results that might harm the company’s reputation or finances.  

For an AI app helping to predict future profit, for example, access to the sales management software is key, along with connections to marketing, human resources, supply-chain, and other operational software to get a full picture of costs throughout the business. Otherwise, the system would be generating outputs on limited information, which could end up giving leaders a false reading of the health of the business.  

Protecting the AI budget  

Identifying all this information across hundreds, maybe thousands of systems takes considerable engineering time and resources. In the event of a hack, if companies don’t have backup copies of these assets, or an understanding of where all their valuable datasets reside, it could mean millions of dollars in wasted investment.  

• Example: Rijksmuseum in Amsterdam; $10 million grant to do high-density, digital x-rays of the “Night Watch” painting; that data set is now worth $10 million.  

Meanwhile, when digital environments go down, the ramifications are widespread. Increasingly, the loss or infection of high-value datasets will hinder employees’ ability to work, and the businesses’ ability to serve customers.  

Whether it’s triaging customer service calls, discovering new sales calls, or helping customers remediate issues, as AI takes on a larger role in customer-facing and operational processes, data outages become more than just IT issues — they are business-critical problems that can trigger operational and reputational backlash.  

Continuous business demands continuous fuel. Protecting data is now about protecting the company itself. To ensure that the energy supply is readily available to power the future, enterprises must make backup and recovery a priority. Without it, companies risk stalling their growth engine. 

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